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The aim of this repository is to show a baseline model for text classification by implementing a LSTM-based model coded in PyTorch. In order to provide a better understanding of the model, it will be used a Tweets dataset provided by Kaggle.

Predicting future temperature using univariate and multivariate features using techniques like Moving window average and LSTM(single and multi step))

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

traffic-prediction using LSTM and GCN by pytorch

Electricity price (energy demand) forecasting using different ML, DL, stacked DL and hybrid methods (XGBoost, GRU, LSTM, CNN, CNN-LSTM, LSTM-Attention, Hybrid GRU-XGBoost and Hybrid LSTM-Attention-XGBoost)..

complete Jupyter notebook for implementation of state-of-the-art Named Entity Recognition with bidirectional LSTMs and ELMo

Sequential data using RNN (LSTM, GRU, etc) CNN and RCNN. Adaptable to variable length input sequence.

PyTorch implementation of deep learning for Raman spectrum recognition: CNN, LSTM, Transformer, GNN and contrastive learning

Machine Learning / Deep Learning with RNN(LSTM, JZS1) - Compose Music, Waltz / 머신 러닝, 딥 러닝, 딥런닝, 딥러닝, 딥 런닝, 작곡, 음악

CNN+LSTM+Attention实现时间序列预测